1. Field of Invention
The present invention relates to data processing systems and methods of processing data. More particularly, the present invention relates to data processing systems which include a data compression encoder and a data compression decoder and methods of processing data which include data compression encoding and decoding.
2. Description of the Prior Art
Data compression encoding is a process which compresses source data into a smaller amount of data representing the information. Typically, data compression encoders operate in accordance with an algorithm to convert the source data into compression encoded data which is typically a much smaller amount of data than the original source data. An example of a compression encoding process is the “WINZIP” application which is used on conventional personal computers to reduce an amount of data which represents a data file. The “WINZIP” application allows a data file to be compression encoded to produce a compressed data file. The compressed data file may therefore be represented for example as a much smaller amount of information on a disc or represented on a smaller number of discs, or communicated via electronic mail which may allow only data files of a limited size.
Another example of compression encoding is compression encoding of video signals represented in digital form in order to substantially reduce an amount of data, or correspondingly a rate of communicating the data which is required to represent the video signals. One example of such video compression encoding algorithms is the Motion Picture Expert Group (MPEG)-type algorithms, and more particularly the MPEG 2 algorithm. The MPEG 2 algorithm is an example of a compression encoding algorithm in which the encoder employs several encoding techniques to compress the amount of data required to represent the video signal. One of these encoding techniques involves dividing the pictures of the video signal into Groups of Pictures (GOPs). At least one of the pictures of the GOP is then divided into smaller groups of pixels known as macro blocks, and a Discrete Cosine Transform (DCT) is applied to the pixels of the macro-blocks. A related coding step involves reducing a level of quantization applied to the coefficients which represent the DCT transformed macro-block in order to reduce an amount of information required to represent the picture in the transform domain without noticeably affecting the image when reproduced by a decoder. Other steps take advantage of spatial and temporal redundancy within the pictures of the GOP in order to send only data representative of changes in the pictures of the GOP from one picture to another. These processing techniques have an advantage of compression encoding the video signals thereby substantially reducing the amount of information required to represent the video signals.
It is often desirable to process the video signal information which is represented in compressed form. Data processing systems, which are arranged to process the information, are therefore provided with a data compression decoder and a data compression encoder. Typically such data processing systems are also provided with a data processor which operates to process the information after the decoder has returned the information into the uncompressed or “base band” form so that the desired processing operations can be performed. Examples of such processing operations performed on compressed video signals are splicing or combining two video signals to produce a composite video signal representative of a mix of two images such as, for example, when a logo is superimposed on a video image. However, when the uncompressed data is recompressed by applying the data compression encoder, an improvement is often provided to the process of data compression re-encoding if parameters or coding decisions which were used in the data compression encoder originally applied to the source data are reused or provided in order to guide the data compression encoder. The encoder uses the parameters, which may represent coding decisions, to re-compression encode the data so that the information which is represented by the uncompressed data is more accurately retained in the recompressed data produced when the data compression encoder is applied to the uncompressed data.
From the aforementioned example of processing video signals, reusing the DCT type and the quantization levels applied to the DCT encoded source data by the compression encoder has an effect of retaining the quality of the video signals when the recompression encoded signal is decompressed and displayed. This is because the data compression re-encoder can match the way in which redundant information is discarded when source data was originally encoded. However, the parameters, which were used in the data compression encoder must be conveyed some how within the data processing system from the data compression decoder to the data compression encoder.
A known technique for conveying the data compression encoding parameters produced from an MPEG 2 type data compression encoder within an uncompressed video signal is known as the MOLE (TM). The MOLE (TM) is described in, for example, a disclosure entitled “Seamless Concatenation—a 21st Century Dream” by M. J. Knee and N. D. Wells, published in a journal entitled “Atlantic Technical Papers”1996-1997 under the Acts AC078 project. It is further specified in a disclosure entitled “Initial Proposal for Video MOLE Standardisation” Essentially, the MOLE provides a technique in which the data compression encoding parameters are incorporated in the least significant bits of the signal samples of the uncompressed video signals as part of the uncompressed data. However, the MOLE is known to have a number of disadvantages. For example, if any processing is performed on the uncompressed data such as, for example, applying a cross fade, the code parameters present within the MOLE will be automatically destroyed and therefore cannot be used for the encoding.